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Forex Trading

The Trader's Guide to Macro Data


Macro economic data is the lifeblood of the Forex markets and whether you are a fundamental or technical trader, it's this data, the changes in sentiment and outlook among your trading peers that drive price action. Simply because FX is all about global macro at heart.

What is macro data?

When we talk about macro data we are usually referring to high level, top down economic data from a specific country or region. Such data can tell us what is going on in an economy as a whole. Through its levels of employment, the balance of payments, consumer spending or indeed business confidence, it provides the observer with a so called "top down" or bird's eye view of a particular facet of an economy. The data will normally cover a specific period, for example, reporting on changes in monthly, quarterly or annual figures.

This information will usually be published in arrears i.e. looking backwards over a prior period even though some survey based data, which is becoming more commonly used, will be forward looking in nature. Expectations about inflation or economic activity are examples of this kind of forward looking data.

Why does macro data matter?

The production of reliable regularly updated statistics and data about a nation state is a key component in the governance of the same. Such data and statistics were first compiled to allow governments to identify, quantify and ultimately tax economic activity and wealth creation in their states. This kind of information gathering dates back to the ancient civilisations of Mesopotamia, Egypt and China. The more complex societies became then the more data that was needed to understand how they operated and how they might be managed.This longer term decline in levels of volatility can be attributed to a relatively static monetary and interest rate policy from the ECB. The ongoing effects of aggressive QE and liquidity provision within the Eurozone along with issues in the European periphery such as Greece and failing Italian and Spanish banks have not caused significant political or financial damage to the Eurozone in recent years.

Modern statistical techniques were first applied to this data in the 19th century, laying the foundation for today's data driven information age. National statistics and economic data have been used by institutional investors to make investment decisions since Victorian times. But as access to the data has been democratised, interest in this data has grown within the wider markets. This was particularly true in the late twentieth century as the data became more freely available online and was updated, as it was published, in real time.

Time series data and the calendar.

Today there are literally hundreds of individual data points that are collected and compiled by national statistical offices, central banks, government departments and trade bodies. To say nothing of proprietary data collected and compiled by brokers, investment banks, research houses and other data providers, this data is collected, processed and presented in what is known as time series. Which quite literally plots the course of change in the data over the observation period. For example, it provides sequential monthly data on the levels of wage growth in an economy.

Because it is standardised, in terms of the periods of observation and data collection, such time series data can be published or released on a regular periodic basis. Leading to the creation of a global, macro economic calendar. And indeed certain data points have today, become harmonised across the major developed economies, in terms of their data capture and release.

The regularity of these data releases creates something of a rhythm in the markets almost like a wave pattern. With periods of high-frequency activity when there are clusters of important data, released close together. And other calmer periods when activity levels drop away as less data or indeed less important data is released.

The image above shows an example of these coordinated data releases with services PMI figures released in China, the Eurozone (and selected member states) alongside those of the UK and the USA. All published in the same business day.

Some data are more important than others.

With so much macro data available there can quite literally be dozens of releases on a weekly or even daily basis. As such the market has learned to rank these data releases and to filter the list in terms of its expected price impact. This creates a distinct hierarchy of releases with the items that the markets pay most attention to being at the top. With less "important" data points falling lower down the list.

At the top of this tree are news items and data points such as interest rate and monetary policy decision that emanate from central banks. Inflation data for both consumers and businesses are in the next tier down alongside items such as unemployment data and details about government budgets, spending, and debts. Economic activity data such as the PMI readings shown in the image above, new orders and trade balances form a further tier. There can also be a hierarchy in terms of frequency of release, monthly data often being seen as more reliable than weekly, data for the same data type. For example, weekly jobless claims are not as highly regarded compared to the corresponding monthly unemployment data in the USA.

There are also trends amongst macro data. For example thirty years ago the control of a nation's money supply was seen as "the" way to control inflation. The data that tracked growth in both broad and narrow measures of money creation (M0, M1, M3 etc ) were therefore closely scrutinised by the markets at that time. But the credit booms in the mid-1990s and early noughties diminished the importance of this data and the emergence of deflation and introduction of QE killed it off completely as an important indicator.

Today outside of interest rate decisions and monetary policy announcements it is US unemployment data, in the form of the monthly Non-Farm Payrolls that holds the markets in thrall. But what's interesting here is that research has shown that although NFP releases grab a great deal of attention from both the media and the markets, the data does not have any long lasting impact on price formation. Whereas information rich survey data releases such as the "Philly Fed" have much larger long term impact on prices perhaps out to 6 months. But they do not usually garner much attention on the day of release.

Leading or lagging indicators

Macro data is in most cases backward looking since it reports what has already happened rather than what is to come. That said some of the data can tell us what is likely to happen in the future, within an economy. This is simply because of where the items measured sit inside the business cycle. These are the so called leading indicators. An example of leading indicators would be durable goods orders; these are new orders placed with manufacturers of hard goods and equipment, by their customers. A rising number of orders suggests expanding economic activity and demand. Whilst a fall in orders could suggest a slowdown or contraction ahead. Consumer confidence is another leading indicator as it sheds light on consumer thinking, motivation, attitudes and how they may act in the future regarding spending etc.

Levels of inventory within businesses are also seen as being predictive of changes in demand. If inventories are seen to be building then demand may be falling. Whilst a drop off in the business inventories of components or raw materials could imply that demand has started to build.

Good examples of lagging indicators are GDP data and inflation measures such as CPI, simply because these two items measure changes that have already happened. That is, historic economic activity and price moves that have already occurred. However, lagging indicators are not simply disregarded by the markets. Rather, they are used to confirm the existence of particular trends and patterns, within a given economy.

There are Lies, damned lies and statistics

Mark Twain's famous quote about the misuse of data to back up an opinion or assumption is a classic but it can hold true today. The validity of some of today's macro data points is hotly debated. No more so than where inflation measures are concerned. For example, core inflation measures often exclude food and fuel prices and may fail to accurately capture the cost of accommodation - three items which are paramount in most people's daily lives. Broader measures of inflation such as CPI or the Consumer Price Index are based on the change in the price of a basket of goods.

The contents of the basket are limited in number and the components vary over time. Calling into question its validity on two counts. GDP data is notorious for subsequent revision. Of course, it's an enormous task to try to measure all the economic activity in an economy. So some retrospective adjustment is to be expected. But in both of these instances, technology, and the shared economy should be able to provide us with more accurate measurements of these and other data items in the not too distant future.

There is also an ongoing debate about the accuracy and validity of much of the economic data that emanate from China. Many of China's state run enterprises are effectively bankrupt but are saved by government subsidies. Which alongside fraud, corruption, and shadow banking all help to distort the data. It's here that leading indicators such as electricity production, freight volumes and other primary sources, such as data from the national accounts play a role in estimating the real levels of growth and economic activity in the People's Republic. When we look at data releases, we need to view the numbers in context and be able to judge what exactly matters to the market because that is what will move FX prices.

Trends in the data

As much of the macro economic data produced by the world's developed and developing economies is produced in time series and to international standards, we can make direct comparisons between both current and historical data and the data sets from two separate countries, or more. Indeed it is this kind of data analysis that informs the models that are an integral part of FX price formation. The perceived narrowing or widening of differentials among key data points are a major driver of investor sentiment and therefore of FX price action. It follows that being able to spot developing trends in macro data is a highly desirable attribute. And because such data is often served in time series, we can do just that.

The image below shows us the trends in unemployment in Italy and Germany over the last decade. We can clearly see the differential signified by the green arrows. But also and perhaps more importantly the trend in the Italian data which is improving despite being unacceptably high. Breaking below horizontal support signified by the blue dashed line and the uptrend in unemployment, shown by the red trendline. Using technical analysis techniques on the charts of fundamental data is not a common thing to do. But I find it works very well for me, in terms of visualising what is actually happening on the ground.

Markets are forward looking and they are more concerned about what's to come rather than what's gone before. As such it's the marginal changes in data and the deviation in that data, from consensus forecasts that holds the markets attention. Large deviations from the consensus forecast for a high impact data point will be likely to cause sharp price fluctuations in related FX pairs and crosses. By the same token monthly changes in a data point such as manufacturing PMI, that either confirm or put pay to a trend, will also elicit a big response in terms of price action.

Traders should familiarise themselves with the major macro data points and the items that they measure. What changes in that data means for the market and their frequency of release.

The Pepperstone economic calendar can help as it can be filtered by currency and expected market impact. Such that if high impact releases linked to the Yen are what interests you, you can filter accordingly.

You won't be able to cover every data point nor should you try. But by keeping track of important data releases that affect the instruments you trade, you will be better prepared and much less likely to be caught on the hop by an unexpected price change.

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